Koon Ho Wong’s lab, University of Macau
Load feature file and data (bw files stored as GRanges object).
# genome feature file
sql_lite_dir <- system.file("extdata","sqllite" , package = "FungalSporeAnalysis")
sql_files <- list.files(path = sql_lite_dir , full.names = T)
names(sql_files) <- basename(sql_files)
# gene lists with expression
gene_list_dir <- system.file("extdata","genesets" , package = "FungalSporeAnalysis")
gene_list_files <- list.files(path = gene_list_dir , full.names = T)
names(gene_list_files) <- basename(gene_list_files)PIC profiles ie. RNAP-II, TBP and TFII-B in spores of A. nidulans generated using genelist_specific_profileplot function.
gene_list <- readr::read_delim(gene_list_files["an_spore_pol2.txt" ], delim="\t", col_names = FALSE)
feature_txDb <- AnnotationDbi::loadDb(sql_files["an_feature_file_s10_m04_r07.sqlite"])
# RNAP-II
pol2_veA_wt_spore <- rtracklayer::import.bw("pol2_veA_wt_spore_mix22_CACAGTTGGT_normalized_repeat.bw")
genelist_specific_profileplot(feature_txDb =feature_txDb,bw_files = "pol2_veA_wt_spore", genelist=gene_list, output_name="An_Spore_Pol2", ymin=3,max_key = 10, min_key = 0, ymax = 5.5, palette = "white_red")
# TBP
veA_wt_TBP_spore <- rtracklayer::import.bw("TBP_veA_wt_spore_mix22_CAGTTGGT_normalized_repeat.bw")
genelist_specific_profileplot(feature_txDb =feature_txDb,bw_files = "veA_wt_TBP_spore", genelist=gene_list,max_key=4.5,min_key = 0, output_name="An_Spore_TBP", ymin=3, palette = "white_green", ymax = 5.5)
# TFII-B
TFIIB_veA_wt_spore <- rtracklayer::import.bw("TFIIB_veA_wt_spore_mix22_CAGTTGGT_normalized_repeat.bw")
genelist_specific_profileplot(feature_txDb =feature_txDb,bw_files = "TFIIB_veA_wt_spore", genelist=gene_list,max_key=5,min_key = 1, output_name="An_Spore_TFIIB", ymin=3, palette = "white_blue", ymax = 5.5)
Distribution of actively transcrbing genes ranked by RNAP-II values in data RNAP-II and RNASeq data.
genelist <- readr::read_delim(gene_list_files["an_spore_pol2_for_percentilelineplot.txt"],delim="\t", col_names=FALSE)
# RNAP-II
pol2_veA_wt_spore <- rtracklayer::import.bw("pol2_veA_wt_spore_mix22_CACAGTTGGT_normalized_repeat.bw")
lineplot_for_bw(feature_txDb, genelist =genelist,bw_file="pol2_veA_wt_spore", output_name = "pol2_veA_wt_spore")
# mRNA levels
An_d3_spore_mRNA_hisat2 <- rtracklayer::import("d3_spore_nidulans_1_hisat2_gencov_normalized.bedgraph")
lineplot_for_bw(feature_txDb, genelist=genelist, bw_file="An_d3_spore_mRNA_hisat2", output_name = "An_d3_spore_mRNA_hisat2", tss=FALSE)Distribution of actively transcrbing genes ranked by RNAP-II values and control genes(non-transcribing genes) in H3 data.
# Histone H3 occupancy
genelist <- readr::read_delim(gene_list_files["an_spore_pol2_for_H3percentile.txt"],delim="\t", col_names=FALSE)
H3_an_spore <- rtracklayer::import("an_spore_H3_AGAACACC_CL1019Mix_normalized.bw")
lineplot_for_bw(feature_txDb, genelist =genelist,bw_file="H3_an_spore", output_name = "H3_an_spore", expression_value = FALSE)
Different histone mark’s occupancy at actively transcribing genes in spore. Here, histone mark signals are normalized to H3. Plots are generated using profiles_normalized_by_control function. First, load RNAP-II signals to rank the histone marks and a genelist of control genes which are lowly transcribing or non-transcribing genes. And then generate normalized profiles of H3Ac, H3K4me3 and H3K36me3 marks.
genelist_1 <- readr::read_delim(gene_list_files["an_spore_pol2.txt"], delim="\t", col_names = FALSE)
genelist_2 <- readr::read_delim(gene_list_files["an_spore_pol2_controlgenes.txt"], delim="\t", col_names = FALSE)
# H3Ac occupancy
H3AC_veA_wt_spore <- rtracklayer::import("An_3d_spore_H3Ac_CGCATTAA_mix33_fang_normalized.bw")
profiles_normalized_by_control(feature_txDb = feature_txDb,bw_test = "H3AC_veA_wt_spore", bw_control = "H3_an_spore",genelist_1 = genelist_1,genelist_2 = genelist_2, ymax = 3.8,ymin=0.5, output_name = "H3Ac_veA_wt_spore")
# H3K4me3
H3K4me3_veA_wt_spore <- rtracklayer::import("veA_wt_spore_H3K36me3_GCGTTTCGA_CL_ChIPmix22_normalized.bw")
profiles_normalized_by_control(feature_txDb = feature_txDb,bw_test = "H3K4me3_veA_wt_spore", bw_control = "H3_an_spore",genelist_1 = genelist_1,genelist_2 = genelist_2, ymax = 6,ymin=0.3, output_name = "H3K4me3_veA_wt_spore")
# H3K36me3
H3K36me3_veA_wt_spore <- rtracklayer::import("veA_wt_spore_H3K4me3_CGGACGTGG_CL_ChIPmix22_normalized.bw")
profiles_normalized_by_control(feature_txDb = feature_txDb,bw_test = "H3K36me3_veA_wt_spore", bw_control = "H3_an_spore",genelist_1 = genelist_1,genelist_2 = genelist_2, ymax = 2,ymin=0.5, output_name = "H3K36me3_veA_wt_spore")
# tRNA feature file
feature_txDb <- AnnotationDbi::loadDb(sql_lite_file["an_feature_file_s10_m04_r07_tRNA.sqlite"])
# tRNA signal file
gene_list <- readr::read_delim(gene_list_files["an_spore_tRNA.txt"], delim="\t", col_names = FALSE)
# TFIII-B
AN3116_HA_spore <- rtracklayer::import("AN3116_HA_spore_GTGGGATAT_ChIPMix49_normalized.bw")
genelist_specific_profileplot(feature_txDb = feature_txDb, genelist = gene_list, bw_files = "AN3116_HA_spore",ymax = 280, ymin = 10, max_key = 59, min_key = 0, output_name = "AN3116_HA_spore", log2 = FALSE, palette = "cream_green")
# TBP
veA_wt_TBP_spore <- rtracklayer::import("veA_wt_TBP_spore_GATCAG_CL_ChIPmix22_normalized.bw")
genelist_specific_profileplot(feature_txDb = feature_txDb, genelist = gene_list, bw_files = "veA_wt_TBP_spore",ymax = 46, ymin = 8, max_key = 59, min_key = 0, output_name = "TBP_veA_wt_spore_tRNA", log2 = FALSE, palette = "cream_green")
# TFIII-C
AN7997_HA_spore <- rtracklayer::import("AN7997_HA_spore_ACGTAGCTCT_ChIPMix49_normalized.bw")
genelist_specific_profileplot(feature_txDb = feature_txDb, genelist = gene_list, bw_files = "AN7997_HA_spore",ymax = 26, ymin = 8, max_key = 59, min_key = 0, output_name = "AN7997_HA_spore", log2 = FALSE, palette = "cream_green")
# Rpo31
AN10316_HA_spore <- rtracklayer::import("AN10316_HA_spore_TGATCCGAT_ChIPMix49_normalized.bw")
genelist_specific_profileplot(feature_txDb = feature_txDb, genelist = gene_list, bw_files = "AN10316_HA_spore",ymax = 270, ymin = 10, max_key = 150, min_key = 0, output_name = "AN10316_HA_spore", log2 = FALSE, palette = "cream_brown")
# Rpc40
AN2415_HA_spore <- rtracklayer::import("AN2415_HA_spore_GCAAGTAGAT_ChIPMix49_normalized.bw")
genelist_specific_profileplot(feature_txDb = feature_txDb, genelist = gene_list, bw_files = "AN2415_HA_spore",ymax = 180, ymin = 10, max_key = 150, min_key = 0, output_name = "AN2415_HA_spore", log2 = FALSE, palette = "cream_brown")
# Rpc11
AN4219_myc_spore <- rtracklayer::import("AN4219_myc_spore_CGAACTGTGT_ChIPMix49_normalized.bw")
genelist_specific_profileplot(feature_txDb = feature_txDb, genelist = gene_list, bw_files = "AN4219_myc_spore",ymax = 225, ymin = 10, max_key = 150, min_key = 0, output_name = "AN4219_myc_spore", log2 = FALSE, palette = "cream_brown")
# rRNA feature file
feature_txDb <- AnnotationDbi::loadDb(sql_files["aniger_feature_file_s01_m07_r09_5SrDNA.sqlite"])
# rRNA signal file
gene_list <- readr::read_delim(gene_list_files["an_spore_5SrDNA.txt"], delim="\t", col_names = FALSE)
# Initiation factors
bw_files <- c("AN3116_HA_spore_niger","veA_wt_TBP_spore_niger", "AN7997_HA_spore_niger")
genelist_specific_profileplot(feature_txDb = feature_txDb, genelist = gene_list, bw_files = bw_files,ymax = 2200, ymin = 0, max_key = 1050, min_key = 0, output_name = "an_spore_initiationfactor_5SrDNA", log2 = FALSE, palette = "cream_green", rename = TRUE)
# RNAP-III subunits
bw_files=c("AN10316_HA_spore_niger","AN2415_HA_spore_niger", "AN4219_myc_spore_niger")
genelist_specific_profileplot(feature_txDb = feature_txDb, genelist = gene_list, bw_files = bw_files,ymax = 2500, ymin = 0, max_key = 1050, min_key = 0, output_name = "an_spore_pol3_5SrDNA", log2 = FALSE, palette = "cream_brown", rename = TRUE)
# A. nidulans
feature_txDb <- AnnotationDbi::loadDb(sql_files["an_feature_file_s10_m04_r07.sqlite"])
bw_files <- c("pol2_veA_wt_spore","input_an_3dspore_polII")
genelist_specific_profileplot(feature_txDb = feature_txDb, genelist = NULL, bw_files = bw_files,top_line = FALSE, max_key = 59, min_key = 0, output_name = "an_pol2_input", log2 = FALSE, palette = "cream_brown", rename = TRUE)
# A. fumigatus
feature_txDb <- AnnotationDbi::loadDb(sql_files["af_feature_file_s03_m05_r07.sqlite"])
bw_files <- c("Af293_spore_2d_polii","input_af_3dspore_polII")
genelist_specific_profileplot(feature_txDb = feature_txDb, genelist = NULL, bw_files = bw_files,top_line = FALSE, max_key = 30, min_key = 0, output_name = "af_pol2_input", log2 = FALSE, palette = "cream_green", rename = TRUE)
# P. marneffei
feature_txDb <- AnnotationDbi::loadDb(sql_files["pm_feature_file_fungiDb41.sqlite"])
bw_files <- c("pm_3day_spore_pol2","input_pm_21dspore_polII")
genelist_specific_profileplot(feature_txDb = feature_txDb, genelist = NULL, bw_files = bw_files,top_line = FALSE, max_key = 30, min_key = 0, output_name = "pm_pol2_input", log2 = FALSE, palette = "cream_pink", rename = TRUE)
dat <- readr::read_delim(gene_list_files["an_spore_hypha_specificgenes.txt"], delim="\t", col_names = TRUE)
input_data <- dat %>% dplyr::filter(class=="spore_maturation")
ggplot_heatmap(input_data ,threshold = TRUE, output_name = "An_spores_maturation_genes_exprsn")
GO enrichment of actively transcribing genes of A. nidulans, A. fumigatus and P. marneffei.
data <- readr::read_delim(gene_list_files["an_af_pm_spores_GO.txt"], col_names = TRUE, delim="\t")
GO_diamondplot(data, output_name = "An_Af_Pm_GO", palette="three_color")GO enrichment of actievly transcribing genes in A. nidulans spores under temperature, salt and Zn- stress.
data <- readr::read_delim(gene_list_files["an_spore_stress_GO.txt"], col_names = TRUE, delim="\t")
data_subset <- data %>% dplyr::filter(class=="4C"|class=="42C")
GO_diamondplot(data=data_subset, output_name = "An_spore_temperature", palette="two_color")
GO enrichment of actievly transcribing genes in A. fumigatus spores under salt and Zn- stress.
data <- readr::read_delim(gene_list_files["af_spore_stress_GO.txt"], col_names = TRUE, delim="\t")
data_subset <- data %>% dplyr::filter(class=="Zn")
GO_diamondplot(data=data_subset, output_name = "Af_spore_Zn", palette="two_color")
feature_txDb <- AnnotationDbi::loadDb(sql_files["an_feature_file_s10_m04_r07.sqlite"])
bw_files <- c("pol2_veA_wt_spore","6day_pol2_spore","17day_pol2_spore")
gene_list <- readr::read_delim(gene_list_files["an_spore_pol2.txt"], delim="\t", col_names = FALSE)
genelist_specific_profileplot(feature_txDb = feature_txDb, genelist = gene_list, bw_files = bw_files,ymax = 62, ymin = 10, max_key = 60, min_key = 0, output_name = "an_pol2_3d_6d_17d", log2 = FALSE, palette = "cream_brown", rename = TRUE)feature_txDb <- AnnotationDbi::loadDb(sql_files["af_feature_file_s03_m05_r07.sqlite"])
gene_list <- readr::read_delim(gene_list_files["af_spore_pol2.txt"], delim="\t", col_names = FALSE)
# plot1: 3-day, plot2: 17-day
bw_files <- c("Af293_spore_2d_polii", "af293_spore_17d_polii")
genelist_specific_profileplot(feature_txDb = feature_txDb, genelist = gene_list, bw_files = bw_files,ymax=30,ymin=10, max_key = 30, min_key = 0, output_name = "af_3day_17day_spore_pol2", log2 = FALSE, palette = "cream_green", rename = TRUE)All the raw fastq files were aligned to reference genomes (e.g. Aspergillus nidulans FGSC A4 reference genome version s10-m04-r03, Aspergillus fumigatus 293 reference genome version s03-m05-r06 and Talaromyces marneffei ATCC18224 reference genome release33) using Bowtie2 (version: 2.2.9). Since annotation of RNAP III is missing from Aspergillus nidulans FGSC A4 reference genome version s10-m04-r03 reads belonging to the 5S rDNA loci wee obtained by mapping to A. niger CBS 51388 genome annotation (version: s01-m07-r09).
For RNASeq, raw reads were aligned to Aspergillus nidulans FGSC A4 reference genome (version: s10-m04-r03) using hisat2 (version: 2.1.0) . Expression level (e.g. FPKM) for each annotated gene was calculated using stringtie (version: 1.3.3b).
RNAP-II and RNASeq correlation was computed using normalised read count over the gene-body. Scatterplot of normalised read count and FPKM values were plotted using scatter plot functionality of FungiExpresZ v0.0.4
For histone marks and TF’s, normalised bw files are compared using multiBigwigSummary function from deeptools.
multiBigwigSummary bins -bs 1000 -b an_spore_H3_AGAACACC_CL1019Mix_normalized.bw an_spore_H3_mix35_TCCAGCCTCT_normalized.bw -outRawCounts an_histone_spore_count_mat.tab --chromosomesToSkip mito_A_nidulans_FGSC_A4 -l an_spore_H3_set1 an_spore_H3_set2dat <- read.delim("inst/extdata/correlation_data/an_histone_spore_count_mat.tab",sep="\t", header = TRUE)
gp <- bw_corr(dat, pattern = ".*_spore_(.*)_(.*)") 4. TF’s
dat <- read.delim("inst/extdata/correlation_data/an_tbp_tf2b_spore_count_mat.tab",sep="\t", header = TRUE)
gp <- bw_corr(dat, pattern = ".*_spore_(.*)_(.*)")